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Positive matches

• 0.027 + - Lexical feature selection
• 0.025 + - Natural language processing
• 0.025 + - Science policy
• 0.017 + - Industry-Academic Partnership
• 0.017 + - PyTorch
• 0.017 + - Public health policy
• 0.017 + - Citation
• 0.017 + - Probability theory
• 0.016 + - Continuous embedding
• 0.015 + - Software engineering in research
• 0.014 + - Software license
• 0.011 + - Software documentation
• 0.009 + - GraphSAGE
• 0.009 + - Edwin Thompson Jaynes
• 0.009 + - Paper
• 0.007 + - Scientific communication
• 0.006 + - Paper/Tshitoyan2019unsupervised
• 0.006 + - NLP
• 0.006 + - Remix
• 0.006 + - Music

Negative matches

• 0.005 + - Softmax function
• 0.002 + - tf-idf
• 0.002 + - Sentiment analysis
• 0.001 + - sense2vec
• 0.001 + - Clinical concept embedding
• 0.001 + - Paper/Hamilton2016
• 0.001 + - Liquid state machine
• 0.001 + - Finkbeiner test
• 0.001 + - Skip-gram
• 0.001 + - Neuron
• 0.001 + - Deep learning
• 0.001 + - Paper/Levy2014
• 0.001 + - Gender bias
• 0.001 + - WordRank
• 0.001 + - wiki2vec
• 0.001 + - Paper/Perozzi2014
• 0.001 + - Ilya Sutskever
• 0.001 + - Chris McCormick
• 0.001 + - Softmax
• 0.001 + - Tomas Mikolov